Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images
Inception Institute of Artificial Intelligence · Wuhan University · +1 more institution
Abstract
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT slices faces several challenges, including high variation in infection characteristics, and low intensity contrast between infections and normal tissues. Further, collecting a large amount of data is impractical within a short time period, inhibiting the training of a deep model. To address these challenges, a novel COVID-19 Lung Infection Segmentation Deep Network (Inf-Net) is…
Citation impact
- FWCI
- 101.94
- Percentile
- 100%
- References
- 105
Authors
8Topics & keywords
- Coronavirus disease 2019 (COVID-19)
- Artificial intelligence
- Computer science
- Segmentation
- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
- Contrast (vision)
- Economic shortage
- Deep learning